Alternatives to esDynamic
Compare esDynamic alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to esDynamic in 2026. Compare features, ratings, user reviews, pricing, and more from esDynamic competitors and alternatives in order to make an informed decision for your business.
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1
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
2
Dataiku
Dataiku
Dataiku is an enterprise AI platform designed to help organizations move from fragmented AI efforts to fully scalable and governed AI success. It brings together people, data, and technology into a single system that enables collaboration between domain experts and technical teams. The platform allows users to build, deploy, and manage AI models, analytics workflows, and AI agents with greater efficiency. Dataiku emphasizes orchestration by connecting data sources, applications, and machine learning processes into unified pipelines. It also provides strong governance capabilities, helping organizations monitor performance, control costs, and reduce risks across AI initiatives. Businesses across industries use Dataiku to modernize analytics, automate workflows, and scale machine learning across teams. With proven results from global enterprises, the platform supports faster innovation and measurable ROI through AI-driven solutions. -
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IBM SPSS Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. Advanced statistical procedures and visualization can provide a robust, user friendly and an integrated platform to understand your data and solve complex business and research problems. • Addresses all facets of the analytical process from data preparation and management to analysis and reporting • Provides tailored functionality and customizable interfaces for different skill levels and functional responsibilities • Delivers graphs and presentation-ready reports to easily communicate results Organizations of all types have relied on proven IBM SPSS Statistics technology to increase revenue, outmaneuver competitors, conduct research, and data driven decision-making.Starting Price: $99/month
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4
Posit
Posit
Posit builds tools that help data scientists work more efficiently, collaborate seamlessly, and share insights securely across their organizations. Its Positron code editor provides the speed of an interactive console combined with the power to build, debug, and deploy data-science workflows in Python and R. Posit’s platform enables teams to scale open-source data science, offering enterprise-ready capabilities for publishing, sharing, and operationalizing applications. Companies rely on Posit’s secure infrastructure to host Shiny apps, dashboards, APIs, and analytical reports with confidence. Whether using open-source packages or cloud-based solutions, Posit supports reproducible, high-quality work at every stage of the data lifecycle. Trusted by millions of users—and more than half of the Fortune 100—Posit empowers professionals across industries to innovate with data. -
5
JetBrains DataSpell
JetBrains
Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.Starting Price: $229 -
6
JupyterLab
Jupyter
Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible, configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular, write plugins that add new components and integrate with existing ones. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include, data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala. -
7
QuantRocket
QuantRocket
QuantRocket is a Python-based platform for researching, backtesting, and trading quantitative strategies. It provides a JupyterLab environment, offers a suite of data integrations, and supports multiple backtesters: Zipline, the open-source backtester that originally powered Quantopian; Alphalens, an alpha factor analysis library; Moonshot, a vectorized backtester based on pandas; and MoonshotML, a walk-forward machine learning backtester. Built on Docker, QuantRocket can be deployed locally or to the cloud and has an open architecture that is flexible and extensible. -
8
Google Colab
Google
Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation and learning. Colab also now offers a Data Science Agent automating analysis, from understanding the data to delivering insights in a working Colab notebook (Sequences shortened. Results for illustrative purposes. Data Science Agent may make mistakes.) -
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MinusX
MinusX
A Chrome extension that operates your analytics apps for you. MinusX is the fastest way to get insights from data. Interop with MinusX to modify or extend existing notebooks. Select an area and ask questions, or ask for modifications. MinusX works in your existing analytics tools like Jupyter Notebooks, Metabase, Tableau, etc. You can use minusx to create analyses and share results with your team, instantly. We have nuanced privacy controls on MinusX. Any data you share, will be used to train better, more accurate models). We never share your data with third parties. MinusX seamlessly integrates with existing tools. This means that you never have to get out of your workflow to answer questions. Since actions are first-class entities, MinusX can choose the right action for the right context. Currently, we support Claude Sonnet 3.5, GPT-4o and GPT-4o mini. We are also working on a way to let you bring your own models. -
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Jupyter Notebook
Project Jupyter
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. -
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Zepl
Zepl
Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github. -
12
MLJAR Studio
MLJAR
It's a desktop app with Jupyter Notebook and Python built in, installed with just one click. It includes interactive code snippets and an AI assistant to make coding faster and easier, perfect for data science projects. We manually hand crafted over 100 interactive code recipes that you can use in your Data Science projects. Code recipes detect packages available in the current environment. Install needed modules with 1-click, literally. You can create and interact with all variables available in your Python session. Interactive recipes speed-up your work. AI Assistant has access to your current Python session, variables and modules. Broad context makes it smart. Our AI Assistant was designed to solve data problems with Python programming language. It can help you with plots, data loading, data wrangling, Machine Learning and more. Use AI to quickly solve issues with code, just click Fix button. The AI assistant will analyze the error and propose the solution.Starting Price: $20 per month -
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JetBrains Datalore
JetBrains
Datalore is a collaborative data science and analytics platform aimed at boosting the whole analytics workflow and making work with data enjoyable for both data scientists and data savvy business teams across the enterprise. Keeping a major focus on data teams workflow, Datalore offers technical-savvy business users the ability to work together with data teams, using no-code or low-code together with the power of Jupyter notebooks. Datalore enables analytical self-service for business users, enabling them to work with data using SQL and no-code cells, build reports and deep dive into data. It offloads the core data team with simple tasks. Datalore enables analysts and data scientists to share results with ML Engineers. You can run your code on powerful CPUs or GPUs and collaborate with your colleagues in real-time.Starting Price: $19.90 per month -
14
Deepnote
Deepnote
Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore, and analyze it with real-time collaboration and version control. Users can easily share project links with team collaborators, or with end-users to present polished assets. All of this is done through a powerful, browser-based UI that runs in the cloud. We built Deepnote because data scientists don't work alone. Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connectionStarting Price: Free -
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Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
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16
Positron
Posit PBC
Positron is a next-generation, free, open source available integrated development environment for data science, built to support both Python and R in one unified workflow. It enables data professionals to move from exploration to production by offering interactive consoles, notebook support, variables and plot panes, and built-in previews of apps alongside code, all without needing extensive configuration. The IDE includes AI-assisted tools like the Positron Assistant and Databot agent to help write or refine code, perform exploratory analysis, and accelerate development. It offers features like a dedicated Data Explorer for viewing dataframes, a connections pane for databases, a variables pane, a plot pane, and seamless switch between R and Python with full support for notebooks, scripts, and visual dashboards. With version control, extensions support, and deep integration with other tools in the Posit Software ecosystem.Starting Price: Free -
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Hex
Hex
Hex brings together the best of notebooks, BI, and docs into a seamless, collaborative UI. Hex is a modern Data Workspace. It makes it easy to connect to data, analyze it in collaborative SQL and Python-powered notebooks, and share work as interactive data apps and stories. Your default landing page in Hex is the Projects page. You can quickly find projects you created, as well as those shared with you and your workspace. The outline provides an easy-to-browse overview of all the cells in a project's Logic View. Every cell in the outline lists the variables it defines, and cells that return a displayed output (chart cells, Input Parameters, markdown cells, etc.) display a preview of that output. You can click any cell in the outline to automatically jump to that position in the logic.Starting Price: $24 per user per month -
18
Streamlit
Streamlit
Streamlit. The fastest way to build and share data apps. Turn data scripts into sharable web apps in minutes. All in Python. All for free. No front-end experience required. Streamlit combines three simple ideas. Embrace Python scripting. Build an app in a few lines of code with our magically simple API. Then see it automatically update as you save the source file. Weave in interaction. Adding a widget is the same as declaring a variable. No need to write a backend, define routes, handle HTTP requests, etc. Deploy instantly. Use Streamlit’s sharing platform to effortlessly share, manage, and collaborate on your apps. A minimal framework for powerful apps. Face-GAN explorer. App that uses Shaobo Guan’s TL-GAN project from Insight Data Science, TensorFlow, and NVIDIA's PG-GAN to generate faces that match selected attributes. Real time object detection. An image browser for the Udacity self-driving-car dataset with real-time object detection. -
19
TestBench
TestBench
TestBench offers an advanced software solution to plan, design, manage, execute, and analyze product tests more efficiently. The tool was designed specifically for software development teams and their test managers, testers, developers, product owners, and stakeholders. Systematic software testing is a demanding and complex task that is time-consuming and resource-intensive but at the same time of crucial importance for the quality of the overall product. This is precisely where TestBench comes in, providing professional tool support to make this process simpler, faster, and of higher quality. TestBench provides support in all phases of the test process – from planning, through design and automation of the tests, to complete logging of the test results. -
20
Illumina Connected Analytics
Illumina
Store, archive, manage, and collaborate on multi-omic datasets. Illumina Connected Analytics is a secure genomic data platform to operationalize informatics and drive scientific insights. Easily import, build, and edit workflows with tools like CWL and Nextflow. Leverage DRAGEN bioinformatics pipelines. Organize data in a secure workspace and share it globally in a compliant manner. Keep your data in your cloud environment while using our platform. Visualize and interpret your data with a flexible analysis environment, including JupyterLab Notebooks. Aggregate, query, and analyze sample and population data in a scalable data warehouse. Scale analysis operations by building, validating, automating, and deploying informatics pipelines. Reduce the time required to analyze genomic data, when swift results can be a critical factor. Enable comprehensive profiling to identify novel drug targets and drug response biomarkers. Flow data seamlessly from Illumina sequencing systems. -
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Plotly Dash
Plotly
Dash & Dash Enterprise let you build & deploy analytic web apps using Python, R, and Julia. No JavaScript or DevOps required. Through Dash, the world's largest companies elevate AI, ML, and Python analytics to business users at 5% the cost of a full-stack development approach. Deliver apps and dashboards that run advanced analytics: ML, NLP, forecasting, computer vision and more. Work in the languages you love: Python, R, and Julia. Reduce costs by migrating legacy, per-seat licensed software to Dash Enterprise's open-core, unlimited end-user pricing model. Move faster by deploying and updating Dash apps without an IT or DevOps team. Create pixel-perfect dashboards & web apps, without writing any CSS. Scale effortlessly with Kubernetes. Support mission-critical Python applications with high availability. -
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Azure Data Science Virtual Machines
Microsoft
DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.Starting Price: $0.005 -
23
Oracle Machine Learning
Oracle
Machine learning uncovers hidden patterns and insights in enterprise data, generating new value for the business. Oracle Machine Learning accelerates the creation and deployment of machine learning models for data scientists using reduced data movement, AutoML technology, and simplified deployment. Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology. Notebooks support SQL, PL/SQL, Python, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. A no-code user interface supporting AutoML on Autonomous Database to improve both data scientist productivity and non-expert user access to powerful in-database algorithms for classification and regression. Data scientists gain integrated model deployment from the Oracle Machine Learning AutoML User Interface. -
24
Metaflow
Netflix
Successful data science projects are delivered by data scientists who can build, improve, and operate end-to-end workflows independently, focusing more on data science, less on engineering. Use Metaflow with your favorite data science libraries, such as Tensorflow or SciKit Learn, and write your models in idiomatic Python code with not much new to learn. Metaflow also supports the R language. Metaflow helps you design your workflow, run it at scale, and deploy it to production. It versions and tracks all your experiments and data automatically. It allows you to inspect results easily in notebooks. Metaflow comes packaged with the tutorials, so getting started is easy. You can make copies of all the tutorials in your current directory using the metaflow command line interface. -
25
Cloudera Data Science Workbench
Cloudera
Accelerate machine learning from research to production with a consistent experience built for your traditional platform. With Python, R, and Scala directly in the web browser, Cloudera Data Science Workbench (CDSW) delivers a self-service experience data scientists will love. Download and experiment with the latest libraries and frameworks in customizable project environments that work just like your laptop. Cloudera Data Science Workbench provides connectivity not only to CDH and HDP but also to the systems your data science teams rely on for analysis. Cloudera Data Science Workbench lets data scientists manage their own analytics pipelines, including built-in scheduling, monitoring, and email alerting. Quickly develop and prototype new machine learning projects and easily deploy them to production. -
26
Bitfount
Bitfount
Bitfount is a platform for distributed data science. We power deep data collaborations without data sharing. Distributed data science sends algorithms to data, instead of the other way around. Set up a federated privacy-preserving analytics and machine learning network in minutes, and let your team focus on insights and innovation instead of bureaucracy. Your data team has the skills to solve your biggest challenges and innovate, but they are held back by barriers to data access. Is complex data pipeline infrastructure messing with your plans? Are compliance processes taking too long? Bitfount has a better way to unleash your data experts. Connect siloed and multi-cloud datasets while preserving privacy and respecting commercial sensitivity. No expensive, time-consuming data lift-and-shift. Usage-based access controls to ensure teams only perform the analysis you want, on the data you want. Transfer management of access controls to the teams who control the data. -
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Neural Designer
Artelnics
Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.Starting Price: $2495/year (per user) -
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Vectice
Vectice
Enabling all enterprise’s AI/ML initiatives to result in consistent and positive impact. Data scientists deserve a solution that makes all their experiments reproducible, every asset discoverable and simplifies knowledge transfer. Managers deserve a dedicated data science solution. to secure knowledge, automate reporting and simplify reviews and processes. Vectice is on a mission to revolutionize the way data science teams work and collaborate. The goal is to ensure consistent and positive AI/ML impact for all organizations. Vectice is bringing the first automated knowledge solution that is both data science aware, actionable and compatible with the tools data scientists use. Vectice auto-captures all the assets that AI/ML teams create such as datasets, code, notebooks, models or runs. Then it auto-generates documentation from business requirements to production deployments. -
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Knoldus
Knoldus
World's largest team of Functional Programming and Fast Data engineers focused on creating customized high-performance solutions. We move from "thought" to "thing" via rapid prototyping and proof of concept. Activate an ecosystem to deliver at scale with CI/CD to support your requirements. Understanding the strategic intent and stakeholder needs to develop a shared vision. Deploy MVP to launch the product in the most efficient & expedient manner possible. Continuous improvements and enhancements to support new requirements. Building great products and providing unmatched engineering services would not be possible without the knowledge and extensive usage of the latest tools and technology. We help you to capitalize on opportunities, respond to competitive threats, and scale successful investments by reducing organizational friction from your company’s structures, processes, and culture. Knoldus helps clients identify and capture the most value and meaningful insights from data. -
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Taipy
Taipy
From simple pilots to production-ready web applications in no time. No more compromise on performance, customization, and scalability. Taipy enhances performance with caching control of graphical events, optimizing rendering by selectively updating graphical components only upon interaction. Effortlessly manage massive datasets with Taipy's built-in decimator for charts, intelligently reducing the number of data points to save time and memory without losing the essence of your data's shape. Struggle with sluggish performance and excessive memory usage, as every data point demands processing. Large datasets become cumbersome, complicating the user experience and data analysis. Scenarios are made easy with Taipy Studio. A powerful VS Code extension that unlocks a convenient graphical editor. Get your methods invoked at a certain time or intervals. Enjoy a variety of predefined themes or build your own.Starting Price: $360 per month -
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Azure DevTest Labs
Microsoft
Quickly provision development and test environments. Minimize waste with quotas and policies. Set automated shutdowns to minimize costs. Build Windows and Linux environments. Provide self-service cloud environments without the worry. Lab policies and thresholds help to effortlessly minimize costs. Set up your virtual machine with your dev tools and your latest build in a few clicks, and share reusable templates across your team. Create environments directly from your continuous integration (CI) tools using our plug-ins, REST API, or Visual Studio Team Services extension. Set lab policies to automatically shut down and start up virtual machines. Set caps on your lab, such as the number of virtual machines per user and per lab. Use the lab cost trend to estimate your spending and set a threshold. Use our REST API to provision dev-test environments directly from your continuous integration (CI) tools. Quickly deploy from your release pipeline using our Team Services tasks extension. -
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Quadratic
Quadratic
Quadratic enables your team to work together on data analysis to deliver faster results. You already know how to use a spreadsheet, but you’ve never had this much power. Quadratic speaks Formulas and Python (SQL & JavaScript coming soon). Use the language you and your team already know. Single-line formulas are hard to read. In Quadratic you can expand your recipes to as many lines as you need. Quadratic has Python library support built-in. Bring the latest open-source tools directly to your spreadsheet. The last line of code is returned to the spreadsheet. Raw values, 1/2D arrays, and Pandas DataFrames are supported by default. Pull or fetch data from an external API, and it updates automatically in Quadratic's cells. Navigate with ease, zoom out for the big picture, and zoom in to focus on the details. Arrange and navigate your data how it makes sense in your head, not how a tool forces you to do it. -
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Tetra Insights
Tetra Insights
Go from user research to shareable video insights in minutes. Automated video clips & highlights. Live Notes for real-time analysis & tagging. Easily upload audio & video content from anywhere. The qualitative data platform for insights-driven organizations. Single source of truth for all of your qualitative data. Spend less time managing and editing media files. We automate the heavy lifting of transcribing and preparing media files for analysis and tagging, so you can focus on generating meaningful insights. Instantly generate research clips and highlights. No more time-consuming and burdensome video editing. Simply tag moments from recordings, and our platform generates clips in real-time. Automatically index research projects. Submit your research plan, and we’ll index your recordings into questions, exercises, and themes so you can easily synthesize research findings without any manual effort.Starting Price: $77 per month -
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Beaker Notebook
Two Sigma Open Source
BeakerX is a collection of kernels and extensions to the Jupyter interactive computing environment. It provides JVM support, Spark cluster support, polyglot programming, interactive plots, tables, forms, publishing, and more. All of BeakerX’s JVM languages plus Python and JavaScript have APIs for interactive time-series, scatter plots, histograms, heatmaps, and treemaps. The widgets remain interactive in both notebooks saved to disk, and notebooks published to the web. They include unique features for handling many points, nanosecond resolution, zooming, and exporting. BeakerX’s table widget automatically recognizes pandas data frames and allows you to search, sort, drag, filter, format, select, graph, hide, pin, and export to CSV or clipboard. This makes connecting to spreadsheets quickly and easy. BeakerX has a Spark magic with GUIs for configuration, status, progress, and interrupt of Spark jobs. You can either use the GUI or create your own SparkSession with code. -
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JupyterHub
JupyterHub
With JupyterHub you can create a multi-user Hub which spawns, manages, and proxies multiple instances of the single-user Jupyter notebook server. Project Jupyter created JupyterHub to support many users. The Hub can offer notebook servers to a class of students, a corporate data science workgroup, a scientific research project, or a high performance computing group. JupyterHub officially does not support Windows. You may be able to use JupyterHub on Windows if you use a Spawner and Authenticator that work on Windows, but the JupyterHub defaults will not. Bugs reported on Windows will not be accepted, and the test suite will not run on Windows. Small patches that fix minor Windows compatibility issues (such as basic installation) may be accepted, however. For Windows-based systems, we would recommend running JupyterHub in a docker container or Linux VM. -
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Obviously AI
Obviously AI
The entire process of building machine learning algorithms and predicting outcomes, packed in one single click. Not all data is built to be ready for ML, use the Data Dialog to seamlessly shape your dataset without wrangling your files. Share your prediction reports with your team or make them public. Allow anyone to start making predictions on your model. Bring dynamic ML predictions into your own app using our low-code API. Predict willingness to pay, score leads and much more in real-time. Obviously AI puts the world’s most cutting-edge algorithms in your hands, without compromising on performance. Forecast revenue, optimize supply chain, personalize marketing. You can now know what happens next. Add a CSV file OR integrate with your favorite data sources in minutes. Pick your prediction column from a dropdown, we'll auto build the AI. Beautifully visualize predicted results, top drivers and simulate "what-if" scenarios.Starting Price: $75 per month -
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RStudio
Posit
RStudio IDE is a powerful integrated development environment built for data scientists using R and Python; it features a console, syntax-highlighting editor supporting direct code execution, plotting, history management, debugging tools, and workspace controls. The open source edition runs on Windows, Mac, and Linux desktops and includes code completion, smart indentation, Visual Markdown editing, project-based working directories, integrated support for multiple working directories, R help and documentation search, interactive debugging, and extensive tools for package development, all under the AGPL v3 license. While the open version provides core capabilities for coding and data exploration, commercial editions add enterprise-grade features like database/NoSQL connections, priority support, and commercial licensing options. RStudio IDE empowers users to analyze data, build visualizations, develop packages, and produce reproducible workflows in a trusted open-source environment.Starting Price: $1,163 per year -
38
Daft
Daft
Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. -
39
Peak
Peak
A new decision intelligence system, putting AI in the hands of commercial leaders to drive great decision making. CODI, our Connected Decision Intelligence system, has been engineered by Peak to become a layer of intelligence that sits between your other systems, unleashing the power of your data for the first time. CODI enables you to quickly deploy AI solutions, harnessing the true potential of your data thanks to its unique full-stack features. It allows data science and data engineering teams to take full control of every aspect of building and deploying AI solutions, at speed and at scale. With CODI, AI projects move beyond being just experiments and become fully-deployed solutions that deliver real world value and results. Built on enterprise-grade infrastructure, CODI is capable of handling data at scale, and seamlessly integrates into existing tech stacks. Surface more insight and combine data from across your organization. -
40
Comet
Comet
Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.Starting Price: $179 per user per month -
41
Cegal Prizm
Cegal
Cegal Prizm is a modular solution designed to allow easy integration of data from different geo-applications, data sources and platforms into a Python environment. The modules allow you to combine geo-data sources for advanced analysis, visualization, data-science workflows, and machine-learning techniques. You can begin to solve problems that were not previously possible with legacy applications. Integrate modern Python technologies to extend, accelerate and augment standard workflows; create and securely distribute customized code, services and technology to a user community for consumption. Connect into the E&P software platform Petrel, OSDU, and other third-party applications and domains to access and retrieve energy data. Seamlessly transfer data locally or across hybrid and cloud deployments to a common Python environment to generate more insight and value. Prizm allows you to enrich datasets with additional application metadata to add more value and context to your analysis. -
42
Cornerstone AI
Cornerstone AI
The traditional system of bespoke data review is not keeping up with the quantity and speed of data. Cornerstone AI has developed a self-learning AI platform to automatically create smarter data rules to clean and organize your data, getting you to better analytical datasets faster. Clinical data that is costing your team time and effort to clean and prepare. Clinical trial, EHR, registry, digital health, claims, image, and sensor data are all supported by our platform. Our platform scans each table and data point, inferring structure and validity. With this, we organize tables for analysis and remove & correct errors in your data. An instant data quality report, highlighting features with most errors. Automated or UI-based correction of those errors, API access to connect directly to your data pipeline, and audit trail for everything. We do not keep, aggregate, or resell your data. Your data is yours and is only used for you. -
43
SquadStack
SquadStack
Our outsourcing platform seamlessly manages your outbound calling efforts with a robust tech stack, artificial intelligence, and on-demand telecallers. Welcome new customers onto your platform and start their onboarding journey. Assist and educate your customers through the entire process of onboarding on your platform to reduce drop-offs. Onboard your gig workforce and engage with them regularly to increase retention and productivity. Reduce disruptions in your delivery lifecycle by reaching out to leads and confirming whether you should reattempt delivery or not, capture correct addresses, etc. Boost your customer experience & reduce RTOs by connecting with your customers over call to confirm COD orders and cancel duplicate ones. Save time and effort by seamlessly setting appointments for your sales team. -
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Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.
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Solvuu
Solvuu
A data science platform for life scientists. Translate your microbiome research into practical applications. Bring novel, safe and effective products to market faster. Integrate the right set of data science and collaboration tools, and achieve rapid advances in cancer therapeutics. Accelerate research, enable innovation and create value by adopting effective digital technology solutions to improve crop productivity. Import your small and big data. Organize according to our templates, or define your own schema. Our format inference algorithm synthesizes parsing functions and lets you override if needed, without coding. Use our interactive import screens or CLI for bulk imports. Your data is not just bytes. Solvuu automatically computes relevant summary statistics and generates rich interactive visualizations. Explore and gain insights into your data immediately; slice and dice as needed. -
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Gathr.ai
Gathr.ai
Gathr is a Data+AI fabric, helping enterprises rapidly deliver production-ready data and AI products. Data+AI fabric enables teams to effortlessly acquire, process, and harness data, leverage AI services to generate intelligence, and build consumer applications— all with unparalleled speed, scale, and confidence. Gathr’s self-service, AI-assisted, and collaborative approach enables data and AI leaders to achieve massive productivity gains by empowering their existing teams to deliver more valuable work in less time. With complete ownership and control over data and AI, flexibility and agility to experiment and innovate on an ongoing basis, and proven reliable performance at real-world scale, Gathr allows them to confidently accelerate POVs to production. Additionally, Gathr supports both cloud and air-gapped deployments, making it the ideal choice for diverse enterprise needs. Gathr, recognized by leading analysts like Gartner and Forrester, is a go-to-partner for Fortune 500Starting Price: $0.25/credit -
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Anaconda
Anaconda
Empowering the enterprise to do real data science at speed and scale with a full-featured machine learning platform. Spend less time managing tools and infrastructure, so you can focus on building machine learning applications that move your business forward. Anaconda Enterprise takes the headache out of ML operations, puts open-source innovation at your fingertips, and provides the foundation for serious data science and machine learning production without locking you into specific models, templates, or workflows. Software developers and data scientists can work together with AE to build, test, debug, and deploy models using their preferred languages and tools. AE provides access to both notebooks and IDEs so developers and data scientists can work together more efficiently. They can also choose from example projects and preconfigured projects. AE projects are automatically containerized so they can be moved between environments with ease. -
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MATLAB
The MathWorks
MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design. -
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FutureAnalytica
FutureAnalytica
Ours is the world’s first & only end-to-end platform for all your AI-powered innovation needs — right from data cleansing & structuring, to creating & deploying advanced data-science models, to infusing advanced analytics algorithms with built-in Recommendation AI, to deducing the outcomes with easy-to-deduce visualization dashboards, as well as Explainable AI to backtrack how the outcomes were derived, our no-code AI platform can do it all! Our platform offers a holistic, seamless data science experience. With key features like a robust Data Lakehouse, a unique AI Studio, a comprehensive AI Marketplace, and a world-class data-science support team (on a need basis), FutureAnalytica is geared to reduce your time, efforts & costs across your data-science & AI journey. Initiate discussions with the leadership, followed by a quick technology assessment in 1–3 days. Build ready-to-integrate AI solutions using FA's fully automated data science & AI platform in 10–18 days. -
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Zerve AI
Zerve AI
Zerve is the agentic data workspace designed for anyone who works with data, from solo analysts, data scientists, business users and teams alike. Zerve brings together exploration, advanced analysis, collaboration, and production deployment into a single AI-native environment, so that important data work doesn’t stall, break, or disappear. Zerve’s AI agents understand the full context of a project and actively help plan, build, debug, and iterate across multi-step analyses. Agents assist with tasks like cleaning and transforming data, identifying issues, and testing approaches, reducing the manual effort that slows teams down. This means working at a higher level of abstraction without being slowed by setup or syntax. Zerve can be used as SaaS, self-hosted, or even on-premise for highly regulated environments. Zerve is used by data professionals in companies such as BBC, QVC, Dun & Bradstreet, Airbus, and many others.Starting Price: $0
